ps: Background publications are not directly tied to the
FormulationMM paper, but they informed the platform's
development. No existing computational data were copied from these
papers into the FormulationMM manuscript.
Understanding the self-assembly and molecular structure of mRNA lipid nanoparticles at real size: Insights from the ultra-large-scale simulation Ruifeng Wang; Yunsen Zhang; Hao Zhong; Jieying Zang; Wei Wang; He Cheng; Yongming Chen; Defang Ouyang *
International Journal of Pharmaceutics 2025 · 670:125114 Understanding the molecular insights of marketed liposomal drugs using molecular dynamics simulations of reduced scale coarse-grained models Ruifeng Wang; Jieying Zang; Hao Zhong; Yunsen Zhang; Defang Ouyang *
npj Drug Discovery 2025 · 2(1):11 Predicting liposome formulations by the integrated machine learning and molecular modeling approaches Han, Run; Zhuyifan Ye; Yunsen Zhang; Yaxin Cheng; Ying Zheng; Defang Ouyang *
Asian Journal of Pharmaceutical Sciences 2023 · 18(3):100811 How can machine learning and multiscale modeling benefit ocular drug development? Nannan Wang; Yunsen Zhang; Wei Wang; Zhuyifan Ye; Hongyu Chen; Guanghui Hu; Defang Ouyang *
Advanced Drug Delivery Reviews 2023 · 114772 In silico formulation prediction of drug/cyclodextrin/polymer ternary complexes by machine learning and molecular modeling techniques Junjun Li; Hanlu Gao; Zhuyifan Ye; Jiayin Deng; Defang Ouyang *
Carbohydrate Polymers 2022 · 275:118712 An integrated computational methodology with data-driven machine learning, molecular modeling and PBPK modeling to accelerate solid dispersion formulation design Hanlu Gao; Wei Wang; Jie Dong; Zhuyifan Ye; Defang Ouyang *
Eur. J. Pharm. Biopharm. 2021 · 158:336–346 Integrated in silico formulation design of self-emulsifying drug delivery systems Haoshi Gao; Haoyue Jia; Jie Dong; Xinggang Yang; Haifeng Li; Defang Ouyang *
Acta Pharm. Sin. B 2021 · 11(11):3585–3594 Computational pharmaceutics — A new paradigm of drug delivery Wei Wang; Zhuyifan Ye; Hanlu Gao; Defang Ouyang *
Journal of Controlled Release 2021 · 338:119–136 Insight into the dissolution molecular mechanism of ternary solid dispersions by combined experiments and molecular simulations Run Han; Tianhe Huang; Xinyang Liu; Xunqing Yin; Haifeng Li; Jiahong Lu; Yuanhui Ji; Huimin Sun; Defang Ouyang *
AAPS PharmSciTech 2019 · 20(7):274 Predicting physical stability of solid dispersions by machine learning techniques Run Han; Hui Xiong; Zhuyifan Ye; Yilong Yang; Tianhe Huang; Qiufang Jing; Jiahong Lu; Hao Pan; Fuzheng Ren; Defang Ouyang *
Journal of Controlled Release 2019 · 311:16–25 Investigation of molecular aggregation mechanism of glipizide/cyclodextrin complexation by combined experimental and molecular modeling approaches Tianhe Huang; Qianqian Zhao; Yan Su; Defang Ouyang *
Asian Journal of Pharmaceutical Sciences 2019 · 14(6):609–620 Predicting complexation performance between cyclodextrins and guest molecules by integrated machine learning and molecular modeling techniques Qianqian Zhao; Zhuyifan Ye; Yan Su; Defang Ouyang *
Acta Pharmaceutica Sinica B 2019 · 9(6):1241–1252 Investigating the molecular dissolution process of binary solid dispersions by molecular dynamics simulations TengIan Chan; Defang Ouyang *
Asian Journal of Pharmaceutical Sciences 2018 · 13(3):248–254 Investigation of molecular dissolution mechanism of ketoprofen binary and ternary solid dispersions by molecular dynamics simulations Weijie Chen; Defang Ouyang *
Molecular Simulation 2017 · 43(13–16):1074–1080 Research advances in molecular modeling in cyclodextrins Qianqian Zhao; Weixiang Zhang; Runmiao Wang; Yitao Wang; Defang Ouyang *
Current Pharmaceutical Design 2017 · 23(3):522–531 Comparison of three molecular simulation approaches for cyclodextrin-ibuprofen complexation Runmiao Wang; Hui Zhou; Shirley W I Siu; Yong Gan; Yitao Wang; Defang Ouyang *
Journal of Nanomaterials 2015 · 16(1):267 Investigating the molecular structures of solid dispersions by the simulated annealing method Defang Ouyang
Chemical Physics Letters 2012 · 554:177–184